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处理诱发电位信号通常采用样本平均方法和维纳滤波法.但前者需要大量的样本,而后者往往需要信号的先验知识,并且计算量很大,难于实时或在线处理.本文将自适应滤波算法用于诱发电位信号的快速处理.计算机模拟结果表明:自适应滤波算法比样本平均法均方误差小,所需的样本数目少.文中也比较了用自适应滤波算法和样本平均法处理人和动物诱发电位的结果.对于受噪声严重干扰的信号,本文指出:把自适应滤波算法和样本平
Usually, the sample-average method and Wiener filter method are used to process the evoked potential signal, but the former requires a large number of samples, which often require prior knowledge of signals and are computationally intensive and difficult to process in real time or online.In this paper, adaptive filtering algorithm Which is used for the rapid processing of evoked potential signal.Computer simulation results show that adaptive filtering algorithm has smaller mean square error than sample average method and less number of samples required.The article also compares adaptive filtering algorithm with sample averaging method Animal evoked potential results.For the signal seriously disturbed by noise, this paper states: the adaptive filtering algorithm and the sample level